Tutorials for SKI/KISS-GP,
Spectral
Mixture Kernels, Kronecker
Inference, and Deep
Kernel Learning. The accompanying code is in Matlab
and is now mostly out of date; the implementations in GPyTorch
are typically much more efficient. However, the
tutorial material and code is still very useful for anyone
wanting to understand the building blocks and practical
advice for SKI/KISS-GP, Spectral Mixture Kernels, or
Kronecker Inference.

SWA is a
simple DNN training method that can be used as a
drop-in replacement for SGD with improved
generalization, faster convergence, and essentially no
overhead. In this repository we provide a PyTorch
implementation of SWA.